Why don’t economists do cost analysis in their impact evaluations?

There isn’t much cost analysis in impact evaluations. In McEwan’s review of 77 randomized experiments in education, he found that “56% of treatments reported no details on incremental costs, while most of the rest reported minimal details.”

At the same time, there are calls for more of this work. As Dhaliwal et al. of J-PAL highlight, cost-effectiveness analysis helps policymakers to weigh the relative benefits of different programs. “One way to encourage policymakers to use the scientific evidence from these rigorous evaluations in their decision making is to present evidence in the form of a cost-effectiveness analysis, which compares the impacts and costs of various programs run in different countries and years that aimed at achieving the same objective.” Recently, Strand & Gaarder blogged about how cost-benefit analysis is key to “getting the most benefit from the money and efforts spent by the World Bank, on its projects and other client support.” As they say, “Every dollar badly spent is a life that wasn’t saved; a child that didn’t receive education.”

Cost analysis, coupled with impact analysis, is valuable to policy decisions. So the recent post by Strand and Gaarder left me considering the question, Why don’t more economists do cost analysis? Even more locally, Why don’t I like to do cost analysis? (And I’ve even done writing on cost analysis – paper; blog post.)

Briefly, let me clarify what I mean by cost analysis. I’m referring to cost-effectiveness and cost-benefit analysis. Cost-effectiveness (CE) analysis examines the cost-per-benefit of an intervention: For example, how much does it cost to achieve an additional standard deviation of student school participation? Cost-benefit (CB) analysis examines the rate of return of an intervention: For example, what is the present value of lifetime benefits of a program set against the costs? The cost side of the analysis is similar across both.

Back to the question: Why don’t economists do it? (Caveats: for the most part; in impact evaluations.)

Reason #1: It doesn’t feel like economics to microeconomists. Or at least, it doesn’t feel that interesting. Microeconomics (where most impact evaluation studies fall) principally concerns itself with decision-making by individuals, households, or firms. So when we have an intervention to provide information about the returns to schooling or to provide agricultural extension classes, we are most interested in the behavior change, or in other words, in the impact of the program. Many multi-arm impact evaluations vary the offered treatment without explicitly or purposely varying the costs to the beneficiaries. So the variation of interest is the variation in behavioral responses.

Of course, costs have non-obvious behavioral implications, i.e., there are non-linearities that make variation in costs much more interesting than “people buy less when the price is higher.” Dupas and Miguel show wide variation in the price elasticity of demand for preventive health products, all from studies that vary the cost to participants.

But most evaluations don’t have lots of price variation, so the cost analysis seems less exciting from an economics standpoint, even though it’s still important from a policy standpoint.

Reason #2: It’s not trivial. A common method of CE/CB analysis is the “ingredients method”; Patrick McEwan has a nice introductory paper here. Essentially, you add up all the cost ingredients of a program and then adjust for “price levels, time preference, and currency.” As my kids would say, easy peasy lemon squeezy.

Not always so easy. There can be a lot of ingredients. Across a set of education impact evaluations compiled by J-PAL, Anna Popova and I identified a median of seven ingredients. And – much more difficult – when an organization or government agency is implementing a wide range of programs, it can be very tricky to deal with all the fixed costs. Impact evaluations of World Bank projects, for example, usually evaluate one or two out of several project activities, and separating costs (beyond the most obvious ones) is non-trivial.

Furthermore, in many settings, understanding the opportunity costs of time for implementers and especially for participants requires a wide range of assumptions.
J-PAL has a nice collection of spreadsheets demonstrating what this can look like, here, with more on methodology here. So it’s possible. But it’s not trivial, and after expending months or years on analyzing the behavioral responses, figuring out these costs can seem overwhelming, and the returns can seem low.

Comments

Interesting read.
I was in a fellowship program (Health Economics) during which we were required to learn about cost analysis (I was looking forward to that module). But when we got to that part, all the facilitator said was that "it's too much work!" So we didn't learn anything beyond basic textbook definitions.I still feel shortchanged! It's definitely something I would want to venture into in future.

As a postdoc, who did my Phd in development but after the dissertation changed to doing cost benefit analysis of early interventions for kids, this post really got me thinking about how to merge my two research areas!

J-PAL website has lots of resources for economists wanting to do cost-analysis with their impact evaluation including spreadsheets for cost collection. The more RCTs that collect costs, the more studies we can include in our comparative CEAs.
https://www.povertyactionlab.org/research-resources/cost-effectiveness

There is a Murphy's Law aspect to this inclusion of costing analysis i.e. OOPs.
Should stakeholders then seek legal recourse in other work seek damages from micro-econometric analytic based CBA estimates, especially when the estimates are way off the mark? If evaulators/ paid consultants are held liable for faulty or overly optimistic (pessimistic) projections on benefits that would have a chilling effect.

Well, CBA has been criticized on several aspects. I am pleased to share some of my recent papers (WPS) on CBA/BCA and Investment Analysis. All these four papers provide better insight into the analysis:
1. A New Method to Estimate IRR and NPV and NPV is not an Appropriate Criterion: https://papers.ssrn.com/abstract=2899648
2. IRR Performs Better than NPV: A Critical Analysis of Multiple IRR and Mutually Exclusive Investments: https://papers.ssrn.com/abstract=2913905
3. The Controversial Reinvestment Assumption in CBA and Capital Investment Analysis: https://papers.ssrn.com/abstract=2918744
4. MIRR is a Spurious criterion and should not be used in cost-benefit analysis and investment analysis http://ssrn.com/abstract=2942456
A summary of the findings follows:
a. A new method is introduced to estimate NPV and IRR from the Capital Amortization Schedule (CAS). The new method is more transparent and explain better the NPV and IRR.
b. The new method exposes that the NPV is the unutilized net cash flow (NCF) and if fully utilized it will become zero at a discount rate equal to IRR. NPV is not a good criterion as it indicate incomplete information on return of capital (ROC) and the return on invested capital (ROIC).
c. IRR is most appropriate to select and rank mutually exclusive investments as explained in the paper listed two.
d. Paper 3 provides evidence that reinvestment of intermediate income in the estimation of IRR is a fallacy and therefore IRR remains as the best criterion. This is again reinforced by the results from paper 1 listed above.
e. MIRR is a spurious criterion because it assumes reinvestment (which is a fallacy) and MIRR also cannot solve the problem of multiple IRR as presumed. MIRR estimate is boundless with increasing investment rate (IR). MIRR is based on modified NCF (MNCF) and the MNCF distorts the cash flow and the results as explained in the paper no; 4 listed above.
Based on these analytical evidence, Investment analysts and decision makers may wish to move away from the conventional wisdom of preferring NPV and using MIRR as a criterion so also the authors of all published works and finance and economic texts.
Appreciate comments.
Regards
Dr Kannapiran Arjunan, Brisbane, Australia

I am pleased to share some of my recent papers (WPS) on CBA/BCA and Investment Analysis. All these four papers provide better insight into the analysis:
1. A New Method to Estimate IRR and NPV and NPV is not an Appropriate Criterion: https://papers.ssrn.com/abstract=2899648
2. IRR Performs Better than NPV: A Critical Analysis of Multiple IRR and Mutually Exclusive Investments: https://papers.ssrn.com/abstract=2913905
3. The Controversial Reinvestment Assumption in CBA and Capital Investment Analysis: https://papers.ssrn.com/abstract=2918744
4. MIRR is a Spurious criterion and should not be used in cost-benefit analysis and investment analysis http://ssrn.com/abstract=2942456
A summary of the findings follows:
a. A new method is introduced to estimate NPV and IRR from the Capital Amortization Schedule (CAS). The new method is more transparent and explain better the NPV and IRR.
b. The new method exposes that the NPV is the unutilized net cash flow (NCF) and if fully utilized it will become zero at a discount rate equal to IRR. NPV is not a good criterion as it indicate incomplete information on return of capital (ROC) and the return on invested capital (ROIC).
c. IRR is most appropriate to select and rank mutually exclusive investments as explained in the paper listed two.
d. Paper 3 provides evidence that reinvestment of intermediate income in the estimation of IRR is a fallacy and therefore IRR remains as the best criterion. This is again reinforced by the results from paper 1 listed above.
e. MIRR is a spurious criterion because it assumes reinvestment (which is a fallacy) and MIRR also cannot solve the problem of multiple IRR as presumed. MIRR estimate is boundless with increasing investment rate (IR). MIRR is based on modified NCF (MNCF) and the MNCF distorts the cash flow and the results as explained in the paper no; 4 listed above.
Based on these analytical evidence, Investment analysts and decision makers may wish to move away from the conventional wisdom of preferring NPV and using MIRR as a criterion so also the authors of all published works and finance and economic texts.
Appreciate comments.
Regards
Dr Kannan Arjunan, PhD (Economics), MBA (Finance), CAIIB Brisbane, Australia

As a management consultant I have been confronted with impact evaluations and to put it in layman's terms I must say 1) The benefits of an intervention, in most cases, continue to accrue over a long time in future therefore CBA becomes tedious and less accurate by making too many assumptions for the future. 2) Behavioral change is indeed the most sought after goal of most the interventions and they have a snowballing effect after a certain period of inertia. It is difficult to project with any accuracy what those effects would be so it becomes like an exercise of fantasy. 3. The benefits cut across sectors. At least in the long run. Again the same problem. So, in my view a more realistic and cogent set of KPIs other than an accounting approach would be a better solution. The KPIs to be set at the beginning of a project after a baseline to benchmark against would be the nearest to accurate and acceptable.